The invention relates to a method for providing an obstacle local terrain map for a vehicle.
It is currently known to capture the local terrain of a vehicle using sensors, such as cameras, lidar, radar or ultrasound. The measurements are frequently represented in a local terrain map (sometimes also referred to as a grid), which comprises cells to which sections of the local terrain (for example 8 cm×8 cm) of the vehicle are assigned. The representation is frequently done by way of indicating with which probability the section of the local terrain which is assigned to the respective cell is occupied by an obstacle. For this reason, this type of local terrain map is also frequently referred to as an occupancy grid. Starting from the local terrain map, many driver assistance systems such as adaptive cruise control (ACC), highly automated driving or emergency brake assist can be realized.
The rule here is that grid-based approaches for local terrain modeling are classically used for “driving” driver assistance functions (for example ACC) and are not used within the parking and parking-maneuvering fields. For “driving” functions, for example on the highway, there is generally an assumption that a planar drivable surface within the capturing range of the sensors or the size of the grid used is present.
When entering the measured distance values of a sensor (for example laser scanner), a distinction must typically be made between actual obstacles above the drivable surface and measurement values on the drivable surface itself. The latter must not be entered into the grid as an actual obstacle. This distinction cannot always be made by the sensor.
The distinction between driving surface and obstacle in this case is typically made on the assumption of an approximately planar drivable surface and simple threshold value formation: All measurement values below a specific height (for example less than 0.2 m) are considered to be assigned to the driving surface and correspondingly not entered in the grid as an obstacle.
However, in particular for parking and parking-maneuvering functions, the assumption of a planar drivable surface frequently does not apply. With respect to the distinction known in the prior art between ground surface and obstacle, for example when approaching an upwardly sloping ramp, at least part of the ramp is identified as an obstacle. This results in the creation of ghost obstacles in places on the road which are actually capable of being driven on. The function of driver assistance functions in this case is strongly limited or erroneous.
DE 10 2011 100 927 A1 describes, among others, the calculation of a segmented, not necessarily flat ground surface based on 3D laser measurements. However, the calculation of the ground surface is based on the sensor measurement values in the form of a point cloud. This method requires a lot of outlay in terms of calculation and storage owing to the use of point measurement values and the real-time demands. With respect to the calculation and memory capacities that are expected of production vehicles nowadays and in the near future, there is currently no expectation that the method proposed there can be carried out in real time. For this reason, it cannot serve as a basis for driver assistance functions either.
U.S. Pat. No. 8,565,958 B1 proposes a cell-based evaluation of sensor measurement values. Here, the respectively lowest height value in a cell is interpreted as the ground value. All height values with a height below a threshold value are intended for ground calculation in the respective cell. This method presupposes that extensive measurement data is available for each cell. Practice has shown that frequently no measurement values are available for major parts of the local terrain. Furthermore, this method for ground determination also operates on individual measurement values of the point cloud. As already explained above, it is currently assumed that such a method is not capable of being performed in real time owing to the expected limited calculation and memory capacities in vehicles.
The invention is therefore based on the object of permitting, in the cases where calculation and memory capacity is limited, the creation of a local terrain map such that correct obstacle identification is possible even in the case of non-planar driving surfaces.
This and other objects are achieved by the method according to the invention, which provides an obstacle local terrain map for a vehicle, specifically a local terrain map which is divided into cells to which in each case an occupancy probability and a corrected obstacle height are assigned. The method includes: providing a starting local terrain map, specifically a local terrain map which is divided into cells to which in each case an occupancy probability and an obstacle height are assigned; for each cell of the starting local terrain map: determining a ground height based on the obstacle heights of the starting local terrain map, wherein the ground height is ascertained by way of smoothing obstacle heights of the starting local terrain map; for each cell of the obstacle local terrain map: determining the corrected obstacle height based on the ground height that was determined for the corresponding cell of the starting local terrain map and on the obstacle height that was assigned to the corresponding cell of the starting local terrain map; determining the respective occupancy probability based on the occupancy probability that was assigned to the corresponding cell in the starting local terrain map; providing the obstacle local terrain map. The starting local terrain map can comprise fewer cells than the obstacle local terrain map, and the starting local terrain map can be part of a larger local terrain map. The height of the ground is here also understood to be an obstacle height.
The method operates with obstacle heights rather than the individual measurements by the sensors, i.e. the point cloud. The obstacle heights are gathered from an evaluation of individual measurements by the sensors which are assigned to a cell. The number of data items is thus reduced compared to the point cloud, and permits, given the expected calculation and memory capacities of typical production vehicles (passenger vehicles), the method to be performed in real time and thus to be used by driver assistance systems. The correction of the obstacle height is performed based on a plurality of obstacle heights of the starting local terrain map and is realized by way of smoothing these values.
The smoothing can be achieved by way of what is known as a pyramid approach, where obstacle heights of neighboring cells are pooled, for example by way of selecting the minimum of the obstacle heights or by way of a (weighted) average. The smoothing can also be carried out with the aid of wavelets or by way of a multiscale approach.
Typically, if the obstacle height that is assigned to the corresponding cell of the starting local terrain map does not differ in terms of a predefined criterion from the ground height that is assigned to the corresponding cell of the starting local terrain map, a value representing the ground is determined for the corrected obstacle height. The defined criterion is, in particular, a height difference between the obstacle height and the ground height according to the starting local terrain map, for example 0.1 m; 0.25 m or 0.3 m.
The difference between the obstacle height of the starting local terrain map and the corresponding ground height is thus considered in the determination of the corrected obstacle height. If said difference is below a threshold value, an obstacle height that represents the ground is assigned to the cell.
The smoothing advantageously takes into consideration obstacle heights of cells of the starting local terrain map which border the cell for which ground height is determined. This approach utilizes the fact that sensors can identify substantially only the front of an obstacle. The major portion of the measurement values and of the obstacle heights of the cells will therefore relate to the measurement of the ground. That means the smoothing is determined substantially by the obstacle heights of those cells that represent local terrain sections in which the road is located. This effect can furthermore be ensured by the smoothing giving dominance to the minimum value of neighboring obstacle heights with respect to greater obstacle heights.
Typically, the ground height is not determined individually for each cell. Instead, in an additional step of the method, a ground surface for all cells of the starting local terrain map is determined: determining a ground surface based on a smoothing of all, or at least a plurality of, obstacle heights of the starting local terrain map. Starting from this ground surface, the ground height in the respectively considered cell is then determined. The ground surface can be given by way of a mathematical representation (for example using reference points), or in fact as a point curve or a point surface.
The ground surface frequently at least partially represents a sloped planar surface and/or a transition between different planar surfaces. The method thus permits correct identification of obstacles even in cases where the vehicle is located for example in front of the start of an upwardly sloping drivable ramp.
In many cases, the sensor measurements will not be able to identify objects or the ground in the associated local terrain sections of each cell, or will not be able to identify them in a sufficient number, with the result that information relating to the height of objects identified there is not available for each cell. For cells in which no information is available relating to the height of objects located there or of the ground, the height information can be set to a previously defined error value. In other words, the obstacle heights of the starting local terrain map and the corrected obstacle heights can in each case also assume an error value which represents that no decisive measurement for the obstacle height is available for the respective cell. In this case, the corrected obstacle height of the corresponding cell of the obstacle local terrain map also assumes this error value.
In one advantageous embodiment, the cells of the obstacle local terrain map represent in each case the same region of the local terrain as the cells of the starting local terrain map. The geometric representation by way of obstacle local terrain map and starting local terrain map is therefore identical.
In a typical implementation, the method furthermore comprises: providing obstacle point measurements which in each case describe the three-dimensional spatial position of a point in the local terrain of the vehicle that was identified as an obstacle; ascertaining the starting local terrain map based on the obstacle point measurements. The sensors of the vehicle, for example lidar sensors or a camera with structure from motion processing, which is known in the prior art, supply the three-dimensional position of points in the local terrain (also on the ground) which were identified, i.e. a 3D point cloud. These identified points are here referred to as obstacle points (and typically also include points on the ground). The individual obstacle points are then assigned to the cells of the starting local terrain map which is previously defined. The assignment is typically effected on the basis of the x/y-coordinates of the obstacle points (i.e. the 2D position of the points, which does not take into account the height information) in comparison with the sections of the local terrain that are represented by cells. As a result, typically a plurality of (for example 5 to 50) obstacle points are assigned to each cell. In order to determine the obstacle height for the respective cell, the height information of the 3D position of the obstacle points is evaluated (z-component). Typically, the obstacle height is determined on the basis of one or more of the following criteria: maximum height information of the obstacle points assigned to a cell; variance of the height information of the obstacle points assigned to a cell; difference between minimum height information and maximum height information of the obstacle points assigned to a cell.
In addition to the obstacle height, what is furthermore determined for each cell is also an occupancy probability which is obtained, in particular, from the number of obstacle points which are assigned to a cell. Here, linear assignment of the number of obstacle points in a cell to an occupancy probability can be effected (with an upper limit, starting from which the occupancy probability is 100%).
Another aspect of the invention relates to a control unit for a vehicle, comprising memory, a microprocessor and electronic interfaces, wherein the control unit is adapted to carry out one of the methods illustrated above. The electronic interfaces can be adapted to establish communication links to sensors of the vehicle and driver assistance systems.
The invention permits the use of grid-based approaches of local terrain capturing with distance-indicating sensor systems also in the parking and parking-maneuvering field when driving on uneven driving surfaces of any shapes which can frequently be found there. It is thus possible to use the advantages of the grid-based approaches even for this use in a favorable manner, which previously was not possible or only to a limited extent. In addition, the illustrated method permits the future use of a common grid for “driving” and “parking,” in which even the “driving” functions are no longer bound to the assumption of a continuous flat plane.
Other objects, advantages and novel features of the present invention will become apparent from the following detailed description of one or more preferred embodiments when considered in conjunction with the accompanying drawings.
Identical reference signs relate to corresponding elements throughout the figures.